It is common to use inflatable occupant restraints, sometimes referred to as airbags, in an automotive vehicle. The deployment of such devices is typically accomplished using a method that determines whether and when operation is appropriate. Currently, there are two prominent methods for deploying an airbag. One relies on jerk, the rate of change of acceleration of a vehicle colliding with another object. This method initiates deployment if and only if it determines that the magnitude of the observed jerk exceeds a prescribed magnitude. The other relies on a collision library, a collection of waveforms that represent simulated accelerations of a vehicle colliding with other objects under different configurations. This method initiates deployment if and only if it determines that the observed waveform correlates favorably with a library acceleration for which deployment is appropriate. As specified, however, both methods have shortcomings. The first relies exclusively on jerk, ignoring both absolute kinetic energy and absolute linear momentum with respect to the ground, or earth. For example, it can deploy inappropriately when jerk is large but changes in energy or momentum are small, conditions that hold for elastic, nearly elastic, and curb collisions at low speeds for which deployment is normally inappropriate. The second relies exclusively on acceleration, also ignoring both energy and linear momentum. For example, it cannot distinguish the difference between identically configured two-body collisions with the same relative velocity but with different energies and momenta. Although the relative velocity and vehicular damage are the same, the energies and momenta provide a way to distinguish the different configurations with respect to the ground. Because the two-body configurations have different ground speeds, they experience different air, road, and control conditions during collisions. Thus, they might require different strategies for deployment. Besides the defects already cited, both methods fail to account for statistical variations in observed data, especially variations inherent in all vehicular collisions.